JP6538834B2 - System for cardiac electrical activity mapping - Google Patents

Description

The present invention relates to a system for cardiac electrical activity mapping . More particularly, the present invention relates to a system for cardiac electrical activity mapping for performing cardiac tissue mapping and / or ablation.

For example, a wide variety of internal medical devices have been developed for medical use for intravascular use. Among these devices are guidewires, catheters and the like. These devices are manufactured by one of a variety of different manufacturing methods and can be used by one of various methods. The known medical devices and methods each have some advantages and disadvantages. There is still a need for providing alternative medical devices, as well as alternative methods for making and using medical devices. The following Patent Document 1 and Non-Patent Document 1 are known as prior art of the present invention.

JP 2012-508079 gazette

CHORRO, Francisco J. et al., Time-Frequency Analysis of Ventral Fibrillation. An Experimental Study, Revista Espanola Cardiologia, 2006, Vol. 59, No. 9, p. 869-878

  The object of the present invention is to identify specific electrode modes and to enable the provision of specific spatial information for targeted therapeutic applications.

The present invention provides alternative designs, materials, methods of manufacture, and uses for medical devices. An exemplary system for mapping cardiac electrical activity includes a catheter shaft. The catheter shaft contains multiple electrodes. The multiple electrode includes a first electrode and a second electrode. The system also includes a processor. The processor may collect a first signal corresponding to the first electrode and a second signal corresponding to the second electrode. Furthermore, the acquisition of the first and second signals takes place over a period of time. The processor also generates a first time-frequency distribution corresponding to the first signal and identifies a first dominant frequency and a first dominant frequency value occurring at a first time, A second time-frequency distribution may be generated that corresponds to the second signal and the second dominant frequency and the second dominant frequency value occurring at the second time may be identified. An attraction point is defined when the first dominant frequency value is substantially associated with the second dominant frequency value. In particular, the processor is configured such that the first dominant frequency value shares a common characteristic with the second dominant frequency value either at a common frequency or at a common point in time. Based on the process of determining an attraction point defined as a characteristic, and a mode that is a characteristic derived from the attraction point to define an electroactivity pattern related to the spatial position of the particular electrode, the targeted treatment The process of identifying a particular spatial location for application may be performed.

Instead of any one of the above-described embodiments, or in addition to any one of the above-described embodiments, the first time - frequency distribution and the second time - the process of generating the frequency distribution is the Fourier transform, short time Use one of Fourier transform or wavelet transform.

Instead of any one of the above-described embodiments, or in addition to any one of the above-described embodiments, the first time - the process of generating a frequency distribution includes a process of generating a spectrogram of the first signal, or , the second time - the process of generating a frequency distribution observed including a process of generating a spectrometer grams of the second signal, or the first time - the process of generating a frequency distribution of said first together comprising a process of generating a spectrogram of the signal, the second time - the process of generating the frequency distribution is Nde contains a process of generating a spectrogram of the second signal.

Instead of or in addition to any of the aspects described above, the first dominant frequency value or the second dominant frequency value may be a maximum frequency value, a chirp signal, a sustained maximum. Equal to at least one of the frequency value and the local maximum frequency value .

Instead of or in addition to any of the aspects described above, the system is capable of determining the dominant frequency threshold, and / or at least one of the maximum frequency value and the local maximum frequency value . One is substantially above the dominant frequency threshold.

  Alternatively or additionally to any of the above mentioned aspects, the processor is configured to determine a dominant frequency threshold. At least one of the maximum frequency value and the local maximum frequency value is substantially above the dominant frequency threshold.

  Instead of or in addition to any of the aspects described above, the first dominant frequency is equal to the second dominant frequency, and the first time point is the first dominant frequency. It is equal to 2 points.

  Specifying a time interval instead of, or in addition to, any of the above mentioned aspects, this time interval comprises the first and second time points, and the second substantially over a period of time And the first dominant frequency value associated with the dominant frequency value.

Instead of or in addition to any of the aspects described above, the processor is configured to identify a time interval, the time interval being the first time point and The first dominant frequency value shares characteristics common with the second dominant frequency value over the time interval, including the second time point.

Alternatively or additionally to any of the above aspects, the processor is configured to collect signals from the third electrode for a time interval , and the processor is configured to : The processor generates a third dominant frequency value, and the processor determines that the first, second, and third dominant frequency values have the common characteristic of either the common frequency or the common time point. It is configured to define the attraction points when sharing.

Alternatively or additionally to any of the above aspects, the processor is configured to identify a frequency interval, the frequency interval being a first dominant frequency value And a second dominant frequency value, wherein the first dominant frequency value shares characteristics with the second dominant frequency value over the frequency interval.

  Instead of or in addition to any of the above mentioned aspects, the system may specify a frequency spacing, which may be a first dominant frequency value and a second dominant frequency value. And a dominant frequency value, wherein the first dominant frequency value substantially relates to the second dominant frequency value over the frequency interval.

  Alternatively or additionally to any of the above aspects, the processor is configured to identify a frequency interval, the frequency interval being a first dominant frequency value and a first dominant frequency value. A first dominant frequency value is substantially associated with the second dominant frequency value over the frequency interval, including two dominant frequency values.

Alternatively or additionally to any of the above aspects, the processor is configured to collect signals from the third electrode for a time interval , and the processor is configured to : Generating a third dominant frequency value, the frequency intervals including the first, second and third dominant frequency values, wherein the first, second and third dominant frequencies are generated The values share common characteristics with one another over the frequency interval.

Alternatively or in addition to any of the above aspects, the processor is configured to generate a visual display , the visual display comprising at least one of: A display of a visual indicator, the visual indicator corresponding to at least one of the first dominant frequency value and the second dominant frequency value.

Instead of or in addition to any of the aspects described above, the processor represents at least one of the first dominant frequency and the second dominant frequency, is configured to generate at least one sinusoidal, processing for generating the visual indication includes a process of displaying the at least one sinusoidal.

Instead of or in addition to any of the aspects described above, the processor represents at least one of the first dominant frequency and the second dominant frequency, At least one phase map, configured to generate corresponding to a phase deviation of at least one of the first dominant frequency and the second dominant frequency over a time interval. , generation of the visual indication includes an indication of the phase map.

  Instead of or in addition to any of the above mentioned aspects, the visual indication comprises an animation corresponding to the first or second dominant frequency, the first or the second The dominant frequency can be varied across multiple heart beats and heart regions.

  Alternatively or in addition to any of the above mentioned aspects, the visual indicator is color, texture or color and texture.

Instead of or in addition to any of the aspects described above, the processor is an animation of at least one of the first dominant frequency and the second dominant frequency. And wherein the visual display is configured to generate one corresponding to a change in at least one of the first dominant frequency and the second dominant frequency over time . including the video.

  Instead of or in addition to any of the above mentioned aspects, generating the visual indication corresponds to at least one of the first and second dominant frequencies, The display of at least one sinusoidal curve, the display of at least one of the phase map and the visual indicator may be color, texture, or color and texture.

  Alternatively or additionally, in addition to any of the above examples, the first signal, the second signal, or the first and second signals include a plurality of modes corresponding to the anatomical region It is.

  Alternatively or in addition to any of the above mentioned aspects, the processor breaks down the modes into different electrical patterns so that a customized treatment can be applied to the anatomical features It is possible.

  Another exemplary system for mapping cardiac electrical activity includes a catheter shaft, a plurality of electrodes coupled to the catheter shaft, and a processor coupled to the catheter shaft. The processor detects a plurality of signals corresponding to a plurality of electrodes, generates a time-frequency distribution for each of the plurality of signals, and identifies a common dominant frequency for one or more electrodes It is possible to take advantage of the common dominant frequency characteristics and to generate a visual display corresponding to the common dominant frequency.

Instead of or in addition to any of the aspects described above, the dominant frequency characteristics include maximum frequency values, chirp signals, sustained maximum frequency values, or local maximum frequency values .

  Instead of, or in addition to, any of the aspects described above, the common dominant frequency occurs at a common dominant point common to one or more of the plurality of electrodes and is common The identification of the frequency includes the determination of the attraction point. Further, the attraction points are defined when common dominant frequency characteristics, common dominant frequencies, and common dominant points are substantially equal.

  Instead of, or in addition to, any of the aspects described above, creating a visual display includes creating a phase map.

  Instead of, or in addition to, any of the aspects described above, the phase map displays one or more sinusoidal curves corresponding to the plurality of signals or derivatives thereof.

  An exemplary method for mapping cardiac electrical activity includes collecting a first signal corresponding to a first electrode and a second signal corresponding to a second electrode. Furthermore, collection of the first and second signals is performed over a time interval, and the first and second signals are collected with a catheter having a plurality of electrodes. The method further comprises generating a first time-frequency distribution corresponding to the first signal, and identifying a first dominant frequency and a first dominant frequency value occurring at a first time point. , Generating a second time-second dominant frequency corresponding to the second signal, and identifying a second dominant frequency and a second dominant frequency value generated at a second time point And determining the attraction points. An attraction point is defined when the first dominant frequency value substantially relates to the second dominant frequency value.

  The above summary of some aspects is not intended to describe each disclosed embodiment or example of the present invention. The figures and the detailed description that follow more particularly exemplify these embodiments.

  While a number of embodiments are disclosed, still other embodiments of the present invention will become apparent to those skilled in the art from the following detailed description, which shows and describes exemplary embodiments of the present invention. . Accordingly, the drawings and the detailed description are to be understood as illustrative in nature and not restrictive.

  The invention may be more completely understood in consideration of the following detailed description in connection with the accompanying drawings, in which:

FIG. 1 is a schematic view of an exemplary catheter system for accessing a target tissue area in the body for diagnostic and therapeutic purposes. FIG. 2 is a schematic view of an exemplary mapping catheter having a basket functional element carrying structure for use in connection with the system of FIG. FIG. 2 is a schematic view of an exemplary functional element that includes multiple mapping electrodes. FIG. 3 shows an exemplary electrogram signal in the time domain and a corresponding frequency representation in the frequency domain. FIG. 7 shows an exemplary time-frequency representation for a single electrode. FIG. 7 shows an example of a two-dimensional time-frequency representation for a single electrode. FIG. 16 shows an example of a two-dimensional time-frequency representation for an electrode of FIG. 7 is an illustration of an example time-frequency representation that includes a single magnitude peak. FIG. 7 is an illustration of an example time-frequency representation that includes a two-step size peak. FIG. 7 is an illustration of an exemplary frequency spectrum that includes peaks of two sizes. FIG. 7 shows an exemplary frequency spectrum including two-step sized peaks having different amplitudes.

  While the present invention can be changed into various modifications and alternatives, the details thereof are shown as an example of the drawings and will be described in detail. However, it should be understood that the invention is not intended to be limited to the particular embodiments described. Rather, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure.

  For the terms defined below, these definitions shall apply, unless a different definition is given in the claims or elsewhere in this specification.

  All numerical values are to be modified by the term "about" whether or not explicitly stated. The term "about" generally refers to a range of numerical values that one of ordinary skill in the art would consider equivalent to the recited values (e.g., having the same function or result). In many cases, the term "about" can include numbers rounded to the nearest significant digit.

  The recitation of a numerical range by endpoints includes all numbers within that range (e.g. 1 to 5 includes 1, 1.5, 2, 2.75, 3, 3.80, 4, and 5) .

  As used in the specification and the appended claims, the singular forms "a", "an" and "the" include plural unless the context clearly dictates otherwise. As used in this specification and the appended claims, the term "or" generally refers to "and / or" at least one of A and B, unless the context clearly indicates otherwise. It is used in the sense of including.

  Terms that refer to references such as "for example," "some embodiments," "other embodiments," etc It should be noted that it is shown to include one. However, such descriptions do not necessarily mean that all aspects include at least one of specific features, structures, and characteristics. In addition, where specific features, structures, and / or characteristics are described in connection with certain embodiments, they are explicitly described unless explicitly stated to the contrary It should be understood that at least one of such specific features, structures, and characteristics may be used in conjunction with other embodiments, whether or not they are present. Also, where at least one of a particular feature, structure, and / or property is described in the context of one embodiment, for another embodiment, at least one of the particular feature, structure, and / or property. It is implied that one contains something missing from all configurations.

  The following detailed description should be read with reference to the drawings, in which like elements in different drawings are identically numbered. The drawings, which are not necessarily to scale, depict exemplary embodiments and are not intended to limit the scope of the present disclosure.

  Electrophysiological mapping of cardiac rhythm disorders often involves introducing a basket catheter (eg, a Boston Scientific Constellation catheter) or other mapping / sensing device with multiple sensors into the heart chamber is connected with. Sensors, such as electrodes, detect physiological signals, such as the electrical activity of the heart, at the sensing location. It is preferable to be able to obtain the electrical activity of the heart which has been processed into an electrogram signal which is related to the sensing location and which accurately represents the excitation of the cells occurring in the heart tissue. Therefore, the processing system analyzes the signal and can output the signal to the display device. In addition, the processing system can output signals as processed outputs, such as static or dynamic activity maps. A user, such as a physician, can perform the diagnostic process using the processed output.

  FIG. 1 is a schematic view of a system 10 for accessing a target tissue region in the body for diagnostic and / or therapeutic purposes. FIG. 1 generally shows a system 10 deployed in the left atrium of the heart. Alternatively, system 10 can be deployed in other areas of the heart, such as the left ventricle, right atrium, or right ventricle. Although the illustrated embodiment shows a system 10 used to ablate myocardial tissue, the present system 10 (and the methods described herein) may alternatively be catheter based. It can be configured for use in ablation of other tissues, such as procedures for cauterizing tissues such as prostate, brain, gallbladder, uterus, nerves, blood vessels and other areas of the body, including systems that do not require .

  System 10 includes a mapping catheter or mapping probe 14 and an ablation catheter or ablation probe 16. Each probe 14 or 16 can be introduced separately into the selected cardiac region 12 through a vein or artery (eg, femoral vein or femoral artery) using appropriate percutaneous access techniques. Alternatively, the mapping probe 14 and the ablation probe 16 can be assembled into a unitary structure for simultaneous insertion and co-deployment in the cardiac region 12.

  The mapping probe 14 may have a flexible catheter body 18. The distal end of the catheter body 18 carries a three-dimensional multi-electrode assembly 20. The structure 20 may take the form of a basket defining an open interior space 22 (see FIG. 2) in the illustrated embodiment, although other multi-electrode structures may be employed. . The structure 20 supports a plurality of mapping electrodes 24 (not explicitly shown in FIG. 1, but shown in FIG. 2), each of which comprises an electrode location on the structure 20 and And a conductive member. Each electrode 24 can be configured to detect or detect, for example, an intrinsic physiological activity represented by an electrical signal in an anatomical region adjacent to the electrode 24.

In addition, the electrodes 24 can be configured to detect activity signals due to intrinsic physiological activity within the anatomical structure. For example, intrinsic cardiac electrical activity may comprise a repeating wave or semi-repetitive wave of electrical activity with a relatively large spike at the onset of an activation event. The electrode 24 can detect such an activation event and the timing of the activation event. In general, the electrodes 24 may detect activation events at different times as the electrical activity waves conduct through the heart. For example, an electrical activity wave may generate an activation event in the vicinity of the first group of detectable electrodes 24 relatively simultaneously, or within a relatively small time limit. As the electrical activity wave conducts the heart, the second group of electrodes 24 detects the activity event of the electrical activity wave at a later time than the first group of electrodes 24. It will be.

  The electrodes 24 are electrically connected to the processing system 32. A signal line (not shown) can be electrically connected to each electrode 24 on the structure 20. The signal line passes through the body 18 of the probe 14 and electrically connects each electrode 24 to the input of the processing system 32. The electrodes 24 sense cardiac electrical activity in an anatomical region, such as myocardial tissue, adjacent to a physical location in the heart. The sensed cardiac electrical activity (e.g., an electrical signal generated by the heart, including an activation signal) is processed to identify one or more sites in the heart suitable for diagnostic or therapeutic procedures, such as ablation procedures, for example. The output can be processed by the processing system 32 to assist the user, eg, a physician, by generating an output-eg, an anatomical map (eg, a vector field map, an activity time map) or a Hilbert transformation map- It is. For example, processing system 32 may generate a near field signal component (eg, an activation signal derived from tissue adjacent to mapping electrode 24) or a disturbing far field signal component (eg, an activation signal derived from non-proximal tissue). It can be identified. In the above example where the structure 20 is located in the atrium of the heart as shown in FIG. 1, the near field signal component may include an activation signal derived from atrial myocardial tissue, The far-field signal component may include an activation signal derived from ventricular myocardial tissue. The near field activity signal component can be further analyzed to find out the presence of the pathology, as well as to determine the appropriate location for ablation (eg, ablation treatment) for treatment of the pathology.

  The processing system 32 may be dedicated circuitry (eg, discrete logic elements and one or more microcontrollers, application specific integrated circuits (ASICs), to perform reception and / or processing on the acquired physiological activity. Alternatively, it may include a specially configured programmable device such as a programmable logic device (PLD) or a field programmable gate array (FPGA). In some embodiments, processing system 32 executes a general purpose microprocessor and a dedicated microprocessor (e.g., processing physiological activity) that execute instructions to receive, analyze, and display information related to received physical activity. To at least one of a digital signal processor (or DSP) optimized for In such an embodiment, processing system 32 may include program instructions capable of performing part of signal processing at runtime. The program instructions may include, for example, firmware, microcode or application code executed by a microprocessor or microcontroller. The embodiments described above are merely exemplary, and the reader will appreciate that the processing system 32 can take any suitable form.

  In addition, the processing system 32 can be configured to measure sensed electrical activity in myocardial tissue adjacent to the electrode 24. For example, in some embodiments, the processing system 32 can be configured to detect cardiac electrical activity associated with a dominant rotor or divergent activity pattern in the mapped anatomical features. For example, at least one of the rotor's path, the rotor's center, and the diverging foci, as at least one of the dominant rotor and the diverging activity pattern plays a role in initiating and maintaining atrial fibrillation. Cauterization is effective in terminating atrial fibrillation. Processing system 32 processes the detected cardiac activity signal to generate an indication of the associated characteristic. The outputs thus processed include isochronous maps, activity time maps, phase maps, action potential duration (APD) maps, Hilbert transform maps, vector field maps, contour maps, reliability maps, electrograms, cardiac activity The potential may be included. Relevant properties help the user to identify a suitable site for ablation treatment.

  Ablation probe 16 includes a flexible catheter body 34 carrying one or more ablation electrodes 36. One or more ablation electrodes 36 are electrically connected to a radio frequency (RF) generator 37 configured to conduct ablation energy to the one or more ablation electrodes 36. The ablation probe 16, like the structure 20, may be movable relative to the anatomical structure to be treated. The ablation probe 16 can be positioned between the electrodes 24 of the structure 20 or adjacent to the electrodes 24 of the structure 20 when the one or more ablation electrodes 36 are positioned at the tissue to be treated is there.

  Processing system 32 may output data to a suitable device, such as display device 40, capable of displaying information associated with the user. In some embodiments, device 40 is a CRT, LED, or other type of display or printer. Display 40 presents the relevant characteristics in a format useful to the user. In addition, the processing system 32 can generate position identification output for display on the device 40 to assist the user in bringing the ablation electrode 36 into contact with the identified tissue site for ablation. .

FIG. 2 shows a mapping catheter , ie, a mapping probe 14, and shows a distal end electrode 24 suitable for use in the system 10 shown in FIG. The mapping probe 14 includes a flexible catheter body 18, the distal end of which can carry a three-dimensional multi-electrode structure 20 having a mapping electrode or sensor 24. The mapping electrode 24 can detect cardiac electrical activity, including activity signals in myocardial tissue. The sensed cardiac electrical activity is processed by the processing system 32 to assist in the identification of a site, ie one or more sites with cardiac rhythm disorder or other myocardial pathology, by generating and displaying relevant characteristics. Be done. This information can also be used to determine the appropriate location for applying an appropriate treatment, such as ablation, to the identified site, and to guide one or more ablation electrodes 36 to the identified site. is there.

  The illustrated three-dimensional multi-electrode structure 20 includes a base member 41 and an end cap 42, and between the base member 41 and the end cap 42, flexible splines 44 as a whole are circumferentially oriented. It is spaced apart and extends. As described herein, the structure 20 can be in the form of a basket that forms an open interior space 22. In some embodiments, the splines 44 are Nitinol®, other metals, silicone rubber, suitable polymers, and other restorative inert materials, each of which is a curved tissue to be contacted. The end cap 42 is connected between the base member 41 and the end cap 42 in a resilient and pre-tensioned state so as to fit on the surface. In the embodiment shown in FIG. 2, eight splines 44 form a three-dimensional multi-electrode structure 20. In other examples, additional or fewer splines 44 can be used. As shown, each spline 44 carries eight mapping electrodes 24. In other embodiments of the three-dimensional multi-electrode structure 20, additional or fewer mapping electrodes 24 can be placed on each spline 44. In the embodiment shown in FIG. 2, the structure 20 is relatively small (e.g., 40 mm or less in diameter). In alternative embodiments, the structure 20 may be smaller or larger (e.g., less than or greater than 40 mm in diameter).

Slidable sheath 50 is movable along the main axis of the lessee ether body 18. The distal movement of the sheath 50 relative to the catheter body 18 causes the sheath 50 to move onto the structure 20, thereby causing the structure 20 to be internal to an anatomical structure such as the heart, for example. It is possible to squeeze into a compact, low profile for insertion and further extraction, or for insertion or extraction. In contrast, when the sheath 50 is moved proximally with respect to the catheter body, the structure 20 can be exposed and elastically expanded back to the free state shown in FIG.

  A signal line (not shown) can be electrically connected to each mapping electrode 24. The signal lines extend to the handle 54 through the body 18 of the mapping catheter (or through the body 18 and further along or through the body 18 or along the body 18), the signal line and the handle 54. May be connected to an external connector 56 that can be configured with a multipole pin connector. An external connector 56 electrically connects the mapping electrode 24 to the processing system 32. It should be understood that this description is merely an example. Some additional details regarding the described and other exemplary mapping systems and methods for processing signals generated by mapping catheters can be found in US Pat. No. 6,070,094, 6, 233, 491, and 6, 735, 465, the disclosures of which are incorporated by reference in their entirety.

  To illustrate the operation of system 10, FIG. 3 is a schematic side view of an example of a basket structure 20 that includes a plurality of mapping electrodes 24. As shown in FIG. In the illustrated example, the basket structure includes 64 mapping electrodes 24. The mapping electrode 24 is divided into eight splines (A, B, C, D, E,...) Divided into eight electrode groups (denoted as 1, 2, 3, 4, 5, 6, 7, 8). They are arranged in each of F, G, and H). Although an arrangement of 64 mapping electrodes 24 disposed on the basket structure 20 is shown, the number of mapping electrodes 24 may alternatively be different numbers in different structures and / or different positions. (One or more of the splines and the electrodes may be arranged in more or less). In addition, multiple basket structures can be arranged on the same or different anatomical structures to obtain signals from different anatomical structures simultaneously.

  After the basket structure 20 has been placed adjacent to the anatomical structure being treated (eg, the left atrium, left ventricle, right atrium, or right ventricle of the heart), the processing system 32 It is configurable to record electrical activity. Moreover, the recorded cardiac electrical activity may be related to the physiological activity of the adjacent anatomical structure. For example, cardiac electrical activity detected by the electrode 24 may include an activation signal indicative of the onset of physiological activity (eg, contraction of the heart). Furthermore, cardiac electrical activity corresponding to physiological activity may be conducted in response to intrinsic physiological activity (eg, an inherently generated electrical signal) or at least one of the multiple electrodes 24 (eg, by a pacing device) Detection based on a preset pacing protocol provided by the

  Although much of the description here relates to the use of the system 10 in the heart, in some cases in addition to at least one of calculations, simulations and theoretical calculations the system 10 in other areas of the body Note that it is available. For example, at least one of neural activity, endocardial and epicardial activity, unipolar measurement, bipolar measurement, both unipolar and bipolar measurement, etc. can be applied to the embodiments. In other words, at least one of the disclosed embodiments and / or techniques is applicable to any electrical measurement and / or any measured or calculated electrical activity.

  The arrangement, size, spacing, and arrangement of each electrode along the constellation catheter and other mapping / sensing devices associated with the geometry specific to the targeted anatomical structure allows the electrode 24 to It may affect the ability (inability) to detect, measure, collect and conduct electrical activity. As mentioned above, the splines 44 of a mapping catheter, constellation catheter, or other similar sensing device are flexible so that these devices have a particular shape and / or posture. Anatomy is adaptable to enemy areas. Furthermore, at any given location within the anatomic region, structure 20 may be manipulated such that one or more splines 44 do not contact adjacent cellular tissue. For example, as the splines 44 twist, bend or fold over each other, the splines 44 separate from nearby cellular tissue. In addition, because the electrodes 24 are disposed on one or more splines 44, it may not be possible to maintain contact with each cell's adjacent cell tissue. The electrodes 24 not maintaining contact with cellular tissue may not be able to perform at least one of sensing, detecting, measuring, collecting and transmitting electrical activity information. Furthermore, because the electrodes 24 can not detect, detect, measure, collect and conduct electrical activity information, the processing system 32 can not accurately display either the diagnostic information or the processed output. For example, either deviation of the required information or incorrect display may occur.

In addition to the above, the electrode 24 may not contact the adjacent cell tissue for other reasons. For example, manipulation of the mapping probe 14 may cause the electrodes 24 to move, which may result in poor contact between the electrodes. Additionally, the electrodes 24 may be disposed adjacent to fibrous tissue, dead tissue, or functionally refractory tissue. Fibrous tissue, dead tissue, or functionally refractory tissue can not perform depolarization and / or response to changes in electrical potential, so these fibrous tissue, dead tissue or functionally impaired tissue The electrode 24 disposed adjacent to the response tissue can not detect a change in potential. Finally, far-field ventricular events and electrical line noise can distort measurements of tissue activity.

  However, electrodes 24 in contact with healthy, capable cell tissue can detect changes in electrical potential in the conducting cell activity waves. Changes in cellular tissue potential can be detected, collected, and displayed as an electrogram. The electrogram may be a visual representation of changes in voltage potential of the cell tissue over time. In addition, it may be desirable to define certain characteristics of the electrical signal as "fiducial" points of the electrical signal. For the purposes of the present disclosure, fiducial points are understood as characteristics of the electrogram that can be used as characteristics to identify cellular activity. The fiducial point may correspond to at least one of peak magnitude, change in slope, and deflection of the electrical signal. It is noted that the fiducial point may include other characteristics of the electrogram or other signal used to generate at least one of the diagnosed output and the processed output. Furthermore, fiducial points may be identified by manual processing by the clinician and / or automated processing by the processing system 32.

  An electrogram representing a change in potential over time can be defined as a visual representation of an electrical signal in the "time domain". However, in general, any electrical signal is understood to have a corresponding representation in the "frequency domain". Transformation methods (eg, Fourier, Fast Fourier, Wavelet, Wigner-Vill) can be used to transform the signal between the time domain and the frequency domain as needed. Also, the electrical signal has a corresponding representation in the analysis area obtained by a transformation such as the Hilbert transformation.

  In addition, in the normally functioning heart, cardiomyocyte discharges are systematically linear. Thus, detecting that the cell's excitation wave is conducting nonlinearly can be viewed as abnormal cellular firing. For example, the generation of cells in the pattern of the rotor indicates the presence of a dominant rotor and divergent activity pattern. Furthermore, since abnormal cell voltage generation appears over the local target tissue area, when the electrical activity is conducted around, in, around, or near the affected or abnormal tissue, the electrical activity is The form, strength or direction may change. Identifying a localized region of these affected tissue or tissue that has caused an abnormality enables the user to be presented with a site for treatment and / or diagnosis. For example, the identification of the area containing the swirl, ie the rotor current, allows the display of the area of the diseased cells or the aberrant cell tissue. Diseased cell tissue or abnormal cell tissue is targeted for ablation procedures. The variously processed outputs, as described above, can be used to identify circular areas, anchorage areas, rotor or other abnormal cell excitation wave conduction areas.

In at least some embodiments, the step of generating the processed output comprises generating a signal from one or more of the 64 electrodes 24 on the structure 20 (eg, a first signal corresponding to the first electrode) And a second signal corresponding to the second electrode). As mentioned above, the detected signals are collected in the time domain and can be displayed. However, in at least one embodiment, the signal displayed in the time domain may be transformed to the frequency domain to further generate a processed output. As mentioned above, transforms such as Fourier transform, fast Fourier transform, or other transforms that generate frequency and power information of the signal can be used to transform the signal between the time domain and the frequency domain. Figure 4 illustrates an exemplary electrogram signal in the time domain 6 1, with frequency the frequency domain representation 62 corresponding thereto.

  Additionally, in some cases, it may be desirable to analyze the frequency representation over time intervals. For example, it may be desirable to analyze the collected signal data as a time-frequency representation. In some cases, the time-frequency representation may be referred to as a spectrogram. For the purpose of the present disclosure, the terms time-frequency representation and spectrogram are used interchangeably.

  The spectrogram can represent the magnitude of the corresponding frequency as the tissue response of the cell changes with time (or other variable). In some cases, transforms such as Fourier transforms, short time Fourier transforms, wavelet transforms, or other transforms that generate frequency and power information on the signal can be used to generate a spectrogram. FIG. 5 shows a three-dimensional visual representation of an exemplary spectrogram 58. The spectrogram 58 corresponds to one exemplary electrode 24 on the multiple electrode structure 20. In FIG. 5, the spectrogram 58 is displayed visually, but the processing system 32 can generate the data necessary to reconstruct the spectrogram without actually producing a visual representation of the spectrogram. But should be understood. Furthermore, the processing system 32 can utilize the collected data independently of the visually displayed spectrogram.

  As shown in FIG. 5, the spectrogram can display a frequency spectrum 60 that varies in size over a range of frequencies 62. In practice, the frequency range 62 is at least one of the original signal, the collected electrical signal, and the frequency range selected by the user. In addition, the processing system 32 can select the range of frequencies for which data is to be utilized from one or more signals collected from the 64 electrodes 24 on the structure 20. For example, a frequency range of 3 to 7 Hz is shown, which is the frequency range in which (hearts) an abnormal cardiac electrical activity occurs. For example, atrial fibrillation can occur mainly in the frequency range of 3 Hz to 7 Hz. Within this frequency range it is also assumed that other abnormal atrial events occur. However, it should be understood that abnormal cardiac activity can occur even in the frequency range other than 3 Hz to 7 Hz.

  In addition, the selected frequency range and / or the filtered frequency range may be greater or less than 3 Hz to 7 Hz (e.g., each limit may be varied from ± 2 Hz to 10 Hz) I want you to understand that. Techniques and / or processed outputs of the embodiments disclosed herein by selecting or ignoring data within a particular frequency range (e.g., depending on the expected range of application) Can be improved. For example, the frequency range may be a narrower range (for example, 3 Hz to 7 Hz, 2 Hz to 10 Hz, 5 Hz to 20 Hz) or a wider range (for example, 0 Hz to 60 Hz, 5 Hz to 100 Hz, 0 Hz to 200 Hz) It may be.

  As shown in FIG. 5, the frequency spectrum 60 corresponds to a portion of the time interval during which the initial electrical signal is detected and collected. Furthermore, the frequency spectrum may change over time intervals. For example, the second frequency spectrum 64 occurs at the second time interval (as compared to the time interval corresponding to the frequency spectrum 62). As shown, frequency spectrum 64 is different from frequency spectrum 60. The difference between frequency spectrum 64 and frequency spectrum 60 may be due to changes in the magnitude of the spectrum relative to frequency values over time. Furthermore, the change in spectral magnitude relative to the frequency value with the passage of time corresponds to the response inherent in the detected and collected original electrical signal.

  In addition to the one displayed in FIG. 5, a two-dimensional spectrogram 66 is shown in FIG. As shown in FIG. 6, the spectrogram 66 can convey the same information as the spectrogram 58. However, the information is presented in different forms. For example, in FIG. 6, the frequency range is displayed on the X axis, while the time interval is displayed on the Y axis. Furthermore, it is possible to visually convey a value indicating the magnitude for each frequency. For example, values indicative of the magnitude may be conveyed by the color spectrum. In other words, the range of colors can indicate the relative magnitude of a given frequency. The embodiments disclosed herein are merely exemplary, and other methods for displaying spectrograms (including frequency variations with respect to time) and / or values indicative of the magnitude of a given frequency may be used. It is conceivable. For example, a value indicating size may be indicated by texture.

  In some cases, the electrical signals sensed and collected by the electrodes 24 may exhibit identical or very similar frequency characteristics over a given time interval. For example, the electrical signal sensed and collected by the electrode 24 may present values indicative of the same or similar magnitude at a given frequency over a given time interval. In other words, a given electrode can sense and collect an electrical signal that exhibits a constant magnitude for a given frequency over a period of time. Furthermore, it is possible to perform display, reproduction and / or specific on the spectrogram for similar frequency characteristics. For example, a spectrogram can transmit a value indicative of a magnitude that matches a given frequency over a time interval.

  FIG. 6 shows an exemplary spectrogram 66 displaying time intervals in which the magnitude values coincide at a given frequency or range of frequencies. For example, at a given frequency, the frequency at which the magnitude values match over a time interval is identified by a solid circle 68. In this embodiment, solid circles 68 indicate values substantially equivalent to one another over a given time interval at the same frequency (indicated by the same cross hatching). In FIG. 6, it can be seen that the exemplary frequency (shown by solid circle 68), which is substantially equivalent in magnitude, is approximately 4.7 Hz. Furthermore, a value indicative of this magnitude occurs over an approximately time interval of 45 ms to 67.5 ms. In some cases, it is noted that the magnitude values are not consistent over a given frequency or time interval.

  As mentioned above, magnitude values may be constant over a single frequency or range of frequencies. As shown in FIG. 6, the magnitude of the frequency is constant over the frequency range of approximately 4 Hz to 5 Hz. In some cases, a single frequency for which the magnitude value is substantially constant may be referred to as a "predominant frequency." Similarly, a frequency band in which the value indicating the magnitude is substantially constant may be referred to as a "predominant frequency band". For example, in FIG. 6, it is possible to regard 4.5 Hz as the dominant frequency. Similarly, it is possible to view 4 Hz-5 Hz as the dominant frequency band. It is understood that in a given spectrogram, one or more dominant frequencies and / or dominant frequency bands may be present.

  Furthermore, it should be understood that the embodiments described above are applicable to one or more electrodes 24 in multi-electrode structure 20. For example, in some cases, it may be desirable to generate one spectrogram for one or more electrodes 24 in multi-electrode structure 20. Additionally, it may be desirable to compare the information provided by the plurality of spectrograms generated for one or more electrodes 24 in multi-electrode structure 20. For example, the size, the dominant frequency, the dominant frequency band, the magnitude, the dominant frequency, and / or the dominant frequency band over the one or more electrodes 24 in the multi-electrode structure 20. It may be preferable to compare at least one of time points and / or time intervals, and further perform association or comparison or association.

  In some embodiments, a unique spectrogram "characteristic" for a single electrode 24 is identified and compared to, correlated with, or compared to a plurality of spectrograms for the remaining electrodes 24 in the multi-electrode structure 20. Or it may be desirable to correlate. In some cases, a unique spectrogram may be referred to as a "mode." It is noted that different properties and modes may be used for comparison with the spectrogram of each electrode 24 in multi-electrode structure 20. For example, a particular characteristic or mode may be a frequency value having the largest magnitude (referred to herein as a "maximum frequency value"), a chirp signal, a sustained frequency value having the largest magnitude (herein " A “maximum frequency value”, a local frequency value having a maximum magnitude (herein referred to as “local maximum frequency value”), and a frequency value having at least one of other advantageous frequency characteristics. It is possible. These are just examples. Other characteristics and modes are also considered. In some cases, a mode may be referred to as a "dominant feature." This dominant property may occur at a frequency called "dominant frequency" and at a point in time referred to as "dominant time". In some cases, the dominant characteristic values (eg, power, amplitude) that occur at frequencies referred to as the "predominant frequency" and at points in time referred to as the "predominant time" are It may be referred to as either "value" or "predominant frequency value representation". Furthermore, in some cases, the mode may be referred to as a "predominant frequency value." In addition, it is taken into account that other user-defined dominant frequency values are defined as modes. In some cases, a single spectrogram for a single electrode may indicate one or more modes identified by the processing system 32.

  In some cases, processing system 32 may group electrodes that exhibit particular characteristics. In addition, the processing system 32 may exhibit electrodes that exhibit specific characteristics only if they have common characteristics at substantially the same frequency and at substantially the same time points or substantially the same time intervals. There are cases where they can be selectively divided into groups. In other words, the processing system 32 may selectively group electrodes that exhibit particular properties if the particular properties of the individual electrodes are substantially interrelated. For example, in some cases, the property used to group the electrodes may be the largest magnitude occurring at a particular frequency. This maximum magnitude occurring at a particular frequency may occur at a single point in time or over a time interval. As mentioned above, the characteristics used to divide the electrodes into groups are the frequency value with the largest magnitude (referred to herein as the "maximum frequency value"), the chirp signal, the largest magnitude. Have a sustained frequency value (referred to herein as the "maximum sustained frequency value"), a local frequency value having the largest magnitude (referred to herein as the "local maximum frequency value"), and other dominant At least one of the local frequency values having a dominant frequency characteristic, which is present in a given spectrogram for any electrode 24.

  In some cases, the processing system 32 can selectively group electrodes that exhibit certain common characteristics that occur at common frequencies and at common points in time or time intervals. In other words, processing system 32 may initially analyze the spectrogram of a given electrode for a particular frequency characteristic (eg, a sustained frequency value having a maximum magnitude, etc.). Once processing system 32 identifies the frequency characteristic, processing system 32 may then determine the frequency and time point at which the frequency characteristic occurred. The processing system 32 determines the frequency characteristics as well as the frequency at which the characteristics occur and the point in time at which the characteristics occur to search for a match with the common characteristics, common frequency, and common time of the initial electrodes. The spectrogram of the electrode 24 can be analyzed. The electrodes with spectrograms showing common characteristics, frequency and time points are then divided into the same group. Common characteristics, frequencies and time points can be called "attraction points". In addition, groupings of electrodes having spectrograms indicating this characteristic, frequency, and time may be referred to as "attraction points".

  In addition, it should be understood that a single spectrogram from a given electrode exhibits one or more features or dominant frequency values over the time interval of the spectrogram. In other words, different types of identifiable features (eg, maximum frequency values present in the spectrogram for any of the electrodes 24, chirp signals, sustained maximum frequency values, local maximum frequency values, and other dominant frequency features). At least one) may occur at different frequencies and at different times. The processing system 32 can analyze, compare, associate, match, and group all one or more electrodes 24. Furthermore, feature matching makes it possible to obtain different attraction points and the resulting mode. In some instances, the mode defines an electroactivity pattern. Further, in some cases, at least one or more modes in the electroactivity pattern may be defined by one or more attraction points, or may include one or more attraction points. In addition, the modes of the electroactivity pattern may correspond to one or more anatomical features.

  FIG. 7 shows an exemplary spectrogram 70 displaying values 72, 74 indicating the largest magnitudes for the two exemplary electrodes. It is to be understood that the characteristics on the spectrogram 70, which are specified for each electrode for the purpose of explanation, are the largest magnitude. However, this property is at least one of the maximum frequency value present on a given spectrogram for any of the electrodes 24, the chirp signal, the sustained maximum frequency value, the local maximum frequency value and other advantageous frequency characteristics. May be

  As shown in FIG. 7, the values 72, 74 (and their occurring frequency and time points) indicating the largest magnitude are identified by the hatching of the illustrated left and right diagonals. In addition, the solid circle 78 shows the frequency and time intervals at which the values 72, 74 indicating the maximum magnitude of both electrodes (as indicated by common cross hatching) substantially coincide. In other words, solid circles 78 indicate that the individual electrodes showing values 72, 74 indicating the largest magnitude share a common magnitude at a common frequency over a common point in time. As mentioned above, this particular combination may be referred to as an attraction point. In addition, the electrodes exhibiting values 72, 74 indicating the largest magnitude can maintain the same mode over this particular time interval. In practice, it should be understood that electrodes exhibiting a particular mode are often spatially related to the multi-electrode structure 20. Thus, in some cases, identifying a particular electrode mode allows for the provision of particular spatial information for targeted therapeutic application. This mode and the corresponding position information also make it possible to indicate the best treatment or to rule out the less effective treatment options for a given situation. Such treatments may include cautery treatment, medication treatment, stimulation treatment, and the like.

  While some embodiments described above determine attraction points as being related to a common characteristic occurring at a common frequency over a common time interval, in other embodiments a single frequency It is noted that the attraction point may be determined as a particular characteristic occurring at a single time interval.

  In addition, the manner in which the frequency characteristics are defined may be varied based on a number of different factors. For example, the particular frequency characteristic may include a threshold that must be met to use that particular characteristic when processing system 32 seeks an attraction point from the spectrogram of electrode 24. In some embodiments that include frequency characteristics associated with the magnitude of the spectral, the threshold may be a minimum expected value that satisfies the characteristics when substantially above the threshold.

  As mentioned above, attraction points can be defined if particular characteristics, ie modes, occurring at particular frequencies and points in time are commonly shared among groups of spectrograms. In addition, attraction points can be defined not only when a characteristic occurs at a single frequency or point in time, but also when a specific characteristic occurs over a range of frequencies or time intervals. For example, in some cases, the processing system 32 identifies an attraction point between two sample electrodes despite the fact that the frequency at which the common characteristic occurs varies between the two electrodes. It is possible. Similarly, in some cases, despite the fact that the point in time at which the common property occurs changes between the two electrodes, the processing system 32 draws the attraction between the two sample electrodes Points can be defined. In addition, in some cases, the processing system 32 has two sample electrodes, despite the fact that both the frequency and time point at which the common property occurs changes between the two electrodes. It is possible to define attraction points in between.

  In some cases, the embodiments described herein are preprogrammed processes to perform, use, or process at least one of steps, methods, operations, and / or algorithms. A system 32 may be included. However, user definition of any given characteristic, value, threshold, etc. is possible. In other words, the processing system may be configured to allow input from a user (e.g., a clinician) involved in particular characteristics and / or input variables. Allowing user-defined input allows the user to "customize" specific algorithms or system outputs.

  As mentioned above, the processing system 32 may perform one or more of the search, targeting and / or selection of one or more specially defined spectrogram characteristics. A given spectrogram may contain one or more modes. For example, FIG. 8 shows an example of a spectrogram 76 of a single electrode 24. Furthermore, FIG. 8 shows the frequency F1 and the magnitude 78 of the peak occurring at the time T1 (corresponding to the value A1 indicating the exemplary magnitude). In the illustrated example, the processing system can perform at least one of peak size 78 search, targeting, and / or selection as a characteristic to compare and identify attraction points across the remaining electrodes 24. is there. Alternatively, the spectra from multiple electrodes can be compared to highlight common characteristic features in the spectra. In some embodiments, a group of electrodes may be directly associated with a particular anatomical feature (e.g., the location of the ventricle). Thus, identifying common spectral features associated with a particular group of electrodes allows identification of corresponding anatomical features.

In some cases, spectrometer grams characteristic of many sets, whereas at least one of a group of different groups of electrodes and overlapping the electrode (and thus, different anatomical features and at least one of overlapping anatomical features Meanwhile In conjunction with The groups of these electrodes corresponding to each anatomical feature can be defined by multiple modes occurring over the same time interval. The multiple modes may be independent of each other or may be dependent (ie, influence each other). Evaluation from local electrode groups, evaluation across all-body electrodes, as each mode is specified and associated with different electrode subgroups, at least one of the identification and association of individual modes among the dependent multiple modes, Evaluations from individual electrodes and / or evaluations from any combination of electrodes can be performed.

  In addition, a given mode can be "degraded" to identify the intrinsic electrical activity that contributes over a particular stage. For example, certain spectrograms may exhibit relatively complex spectral patterns (eg, spectrogram characteristics, modes, etc.) in both frequency and time. Through the decomposition process, it is possible to remove one or more modes from this complex pattern. This correlates to a particular pathology, thus allowing the identification of particular patterns treatable based on the pathology that could not be identified before. In other words, processing techniques are applicable to those that correlate to particular modes with particular electrical patterns. For example, processing techniques may determine that a particular mode correlates to the rotor, ectopic electrical activity, etc., with different relative powers that vary with time. Furthermore, these patterns are broken down into modes over time and are targeted for specific treatments.

  In some cases, the particular type of pathology observed (eg, arrhythmia) is a coordinated result of dominant and secondary dominant modes. Understanding the association between multiple modes allows an indication of whether to process one or more specific electrical patterns (corresponding to one or more modes).

  For example, a given dominant spectral feature is recognizable as (on its surface) a target mode. However, in reality, the observed spectral properties may include multiple sub-dominant modes that contribute to the electrical pattern over time. Furthermore, multiple modes (eg, dominant mode and secondary dominant mode) affect each other's manifestation with different relative powers over time. In this case, it may be preferable to use decomposition techniques to identify the presence of two distinct modes and to identify the underlying electrical pattern corresponding to the distinct modes. Furthermore, it is possible to specialize the treatment to a specific medical condition that corresponds to the individual mode and the electrical pattern.

However, in some cases, spectrometer grams characteristics (e.g., magnitude of the peak) may processing system 32 contains one or more characteristics that can not be identified first. For example, FIG. 9 shows such an exemplary spectrum 76. However, as can be seen from FIG. 9, the peak magnitude 78 may (in fact) include two separate peak magnitudes 80, 82 occurring at exemplary frequencies F1 and F2, respectively. is there. It should be understood that the frequencies F1 and F2 are very close in value and, as such, are difficult to determine by the processing system 32 during the initial processing steps.

In some cases, it may be desirable for processing system 32 to further refine the frequency spectrum signal in order for processing system 32 to accurately select, group, and define attraction points. For example, the values 80, 82 indicating the magnitudes of peaks shown in FIG. 9 may reflect frequency values that occur at frequencies derived from pathologies of two different cells (eg, arrhythmia). In that case, if the values 80 and 82 indicating the magnitude of the peak are grouped into at least one of the same attraction point and mode, there is a possibility that the values become inaccurate. Furthermore, electrodes spectrometer grams 76 is derived may be grouped into two different modes corresponding to two distinct peak frequencies two peak frequency value is generated. Therefore, in order to determine the attraction points or mode more precisely, signal processing techniques (e.g., frequency estimation techniques) applied to, be made refinement or adjustment contributes frequency spectrum signal to a given spectrometer grams preferable. In some embodiments, the frame of the time-frequency representation can be expanded in the time axis, thus providing a higher resolution in frequency.

  In some embodiments, it may be desirable to utilize harmonic components of a given frequency spectrum for refinement or adjustment of the frequency spectrum. For example, it is also possible to incorporate power values of integral multiples of any fundamental frequency (e.g. dominant frequency, frequency with which the maximum frequency value occurs, etc.). Furthermore, the value of the power generated at integer multiples of the fundamental frequency is combined with the fundamental frequency, whereby the relative measurement of the relative power or the power or magnitude of the relative harmonic spectrum as a function of the fundamental frequency It is also possible to generate an adjusted measurement value. This measurement produces a peak at a frequency corresponding to that of the inherent periodicity, which is assumed to be an adjustment or refinement of the fundamental frequency.

  In addition, the present technique uses one or more frequencies corresponding to the frequency spectrum to adjust frequency values along a portion or the entire portion of the frequency spectrum that produces what can be referred to as a "periodic spectrum" Is possible. Thus, the present technology is capable of providing the difference between the magnitudes of closely related frequency peaks. In some embodiments, the technology can be an application of comb filters that filter signals, signal differences, and / or frequency spectra. In addition, it is possible to apply the present technique over the frequency spectrum of the entire time interval of a given spectrum, resulting in a time frequency representation of the periodic spectrum. In some cases, comb filters can be applied directly to one or more attraction points.

  FIG. 10 shows a two-dimensional view of the frequency spectrum 90 of FIG. 9 including two peak sizes 80 and 82 and harmonic peaks 84 and 86 appearing at initial integer multiples of each of the peak sizes 80 and 82. The representation 88 is shown. As mentioned above, a value 84 is added to the peak magnitude 80 indicating the magnitude occurring at the first integer multiple F3 (ie 2 × F1) of the fundamental frequency F1 (corresponding to the peak magnitude 80) May be preferred. In addition, it may be desirable to add a value 86 indicative of the magnitude generated at the first integer multiple F4 (e.g. 2 x F2) to the value of the peak magnitude 82. Because the values indicating the magnitudes occurring at integer multiples may be different, adding their respective values to the corresponding fundamental frequency would be to subtract the values indicating the magnitudes of the peaks for the fundamental frequency. Become. This exemplary description uses the first integer multiples F3, F4 of the fundamental frequencies F1, F2 (e.g. 2xF1, 2xF2). However, it is assumed that frequency values occurring at additional integer multiples (e.g. 3, 4, 5, 6, 7 etc) are added to the further subtracted fundamental frequency values. As an illustration, FIG. 10 shows the dominant peak 92 occurring at non-integer multiple F5.

  FIG. 11 shows the difference between the peak sizes 80, 82 after adding the magnitude values 84, 86 to the fundamental frequency values generated at frequencies F1 and F2. As shown, the size peaks 80, 82 are longitudinally separated from one another. This difference allows processing system 32 to more accurately identify and group frequency vector characteristics. Specifically, it allows the choice of whether the processing system 32 includes or excludes the frequency spectrum 88 from which one or more modes are derived.

  As shown in FIG. 11, after the peak sizes 80 and 82 are added, the values 84 and 86 indicating the sizes substantially indicate the values 80 and 82 indicating the sizes in FIG. It is subtracted for both 84 and 86. In addition, with respect to the magnitude values 80, 82, the value of the dominant peak 92 (corresponding to the non-integer multiple F5) is substantially subtracted from the corresponding value of FIG. In addition, for the magnitude values 80, 82 (as shown in FIG. 11), the values showing the baseline magnitude between peaks 84, 86 and 92 are shown (as shown in FIG. 10). There is a downward trend as the frequency increases (in comparison to the magnitude value).

  The harmonic techniques disclosed herein (e.g. including the use of filters such as comb filters) may be performed before an attraction point is identified, after an attraction point is identified, or before or after the attraction point is identified. It is considered that it is applicable. It is also taken into account that harmonic techniques can be applied to the combined spectrum from multiple electrodes. Furthermore, it is noted that one or more peak sizes may be included in the attraction point after harmonic techniques have been applied and peak sizes have been identified. Similarly, one or more peaks can be excluded from attraction points.

  In addition, after the processing system 32 determines the attraction points and modes, the processing system 32 may use the attraction points and modes to create a diagnostic display corresponding to the spatial relationship of the electrodes corresponding to the attraction points and modes. The generated frequency is available.

  For example, processing system 32 may determine at least one of an attraction point collected from electrode 24 of structure 20, a sinusoidal curve of the mode, and a phase value that correlates to a dominant frequency. For example, the Fourier transform can determine and generate sinusoidal curves, phase values, for each electrode 24 at a selected frequency (eg, attraction point and / or mode frequency). is there. Alternatively, such sinusoidal curve models can be evaluated for each electrode 24 by using evaluation techniques well documented in the field of signal processing technology, and the time epochs associated with the attraction points Is applicable to electrode waveforms. Furthermore, each corresponding sinusoidal curve derived with a phase shift is a dynamic "moving image" or "dynamic" corresponding to the particular attraction point and / or mode from which the selected frequency was derived. Available to generate a 'map'. The animation or dynamic map provides a medium that allows better visualization of waveform conduction and / or focal impulses in certain pathologies through a summary of properties (e.g. activity time, phase etc) to enable. In some embodiments, a visual indication (eg, animation, dynamic map, topological map, etc.) can be drawn on the anatomical representation of the ventricle of interest. In addition, visual displays (eg, motion pictures, dynamic maps, phase maps, etc.) are the first dominant frequency values that change across multiple heartbeats and parts or ventricles of the various hearts, and second dominant It is possible to correspond to the frequency value or any one of them. Some further details regarding creating a dynamic phase map from a sinusoidal representation are described in a US patent application entitled "Medical Device for Cardiac Tissue Mapping" (Lawyer No. 1001.3562100). .

  Processing system 32 is capable of selectively erasing any of the collected signals in implementing the techniques and / or embodiments disclosed herein. For example, it would be beneficial to eliminate the signal collected by an electrode that is not in electrical contact with, or in poor electrical contact with the excitable tissue of the heart. Such signals may not provide useful information and may distort the results of the above-described techniques.

  Alternatively, instead of eliminating collected signals that do not provide useful information, processing system 32 may alternatively interpolate and estimate values for signals that do not otherwise provide the desired information. In order to perform at least one of better processing, determination and / or generation of useful processed data, or to smooth, refine or present useful processed data in a more preferable manner The processing system 32 can use interpolation and estimation of data.

  It is noted that the methods disclosed herein can be complementary over multiple beats, arousals, or cardiac pacing time intervals. Furthermore, multiple beats and / or multiple excitement can be analyzed by using statistical methods or applying the disclosed method. For example, activation times can be collected over a series of heartbeats or pulses. The statistical distribution of activity times collected can be calculated, analyzed and integrated in the disclosed method.

  This disclosure is, in many respects, only illustrative. In particular, it is possible to change in detail the shape, size and arrangement of the steps without departing from the scope of the present invention. This may include the use of any of the features of one embodiment used in other embodiments, as it is appropriate. The scope of the invention is, of course, defined in the language in which the appended claims are expressed.

  Various modifications and additions can be made to the described exemplary embodiments without departing from the scope of the present invention. For example, while the embodiments described above refer to particular features, the scope of the present invention also includes embodiments having different combinations of features and embodiments that do not include all of the described features. Accordingly, the scope of the present invention is intended to embrace all such equivalents, as well as all such alternatives, modifications and variations that fall within the scope of the claims.

Claims (15)

A system for cardiac electrical activity mapping,
A catheter shaft to which a plurality of electrodes including a first electrode and a second electrode are connected;
A processor, the processor being
Collecting over a time interval a first signal corresponding to the first electrode and a second signal corresponding to the second electrode;
Generating a first time-frequency distribution corresponding to the first signal;
Said first time - a first processing for identifying the dominant frequency value generated in the first dominant frequency in the first time point in the frequency distribution,
Generating a second time-frequency distribution corresponding to the second signal;
The second time - a process of identifying a second dominant frequency values occurring at a second dominant frequency at a second time point in the frequency distribution,
An attraction point defined as a characteristic of a particular electrode when the first dominant frequency value shares a common characteristic with either the common frequency or the common point with the second dominant frequency value. The process to decide
A process for identifying a particular spatial location for targeted treatment application based on a mode that is a characteristic derived from the attraction point to define an electrical activity pattern related to the particular electrode's spatial location When,
The system is executable. It said first time - frequency distribution and the second time - the process of generating the frequency distribution is the Fourier transform, using a single short-time Fourier transform, or wavelet transform, the system according to claim 1. It said first time - the process of generating a frequency distribution includes a process of generating a spectrogram of the first signal, or the second time - the process of generating a frequency distribution of the second signal Spectrometer look including a process of generating grams, or the first time - with the process of generating a frequency distribution includes a process of generating the spectrogram of the first signal, the second time - generating a frequency distribution process are Nde contains a process of generating a spectrogram of the second signal, the system according to claim 1 or 2. The first or second dominant frequency value is equal to at least one of a maximum frequency value, a chirp signal, a sustained maximum frequency value, and a local maximum frequency value . The system according to any one of the preceding claims. Wherein the processor is configured to determine a frequency threshold, said at least one of the maximum frequency value and the local maximum frequency value is more than the frequency threshold value, according to claim 4 system.   6. The system according to claim 1, wherein the first dominant frequency is equal to the second dominant frequency and the first time point is equal to the second time point. The processor is configured to identify a time interval, the time interval including the first time point and the second time point, and the first dominant frequency value is the time interval. The system according to any one of the preceding claims , sharing common characteristics with the second dominant frequency value over The processor is configured to collect a signal from a third electrode over a time interval, the processor generating a third dominant frequency value, and the processor is configured to: 2. The method according to claim 1, wherein the attraction point is defined when the second and third dominant frequency values share the common characteristic of either the common frequency or the common point of time. The system according to any one of 7. The processor is configured to identify a frequency interval, the frequency interval comprising a first dominant frequency value and a second dominant frequency value, the first dominant frequency value being A system according to any one of the preceding claims , sharing characteristics common to the second dominant frequency value over the frequency interval. The processor is configured to collect a signal from a third electrode over a time interval, the processor generating a third dominant frequency value, the frequency interval comprising: 10. A method according to claim 1, comprising second and third dominant frequency values, wherein the first, second and third dominant frequency values share common characteristics with one another over the frequency interval. The system according to any one of the preceding claims. The processor is configured to generate a visual display, the visual display including a display of at least one visual indicator, the visual indicator being the first superior 11. A system according to any one of the preceding claims, corresponding to at least one of a frequency value and the second dominant frequency value. Wherein the processor is to represent at least one of the first dominant frequency and the second dominant frequency is configured to generate at least one sinusoidal, the visual indication process resulting includes processing for displaying the at least one sinusoidal system of claim 11. The processor is at least one phase map representing at least one of the first dominant frequency and the second dominant frequency, the first dominant frequency and the first dominant frequency over a time interval. 12. The method according to claim 11 or claim 14, wherein the generation of the visual indication comprises displaying the phase map, wherein the generation of the visual indication comprises generating an indication corresponding to a phase deviation of at least one of the two dominant frequencies. The system according to 12.   The system according to any one of claims 11 to 13, wherein the visual indicator is color, texture or color and texture. The processor is a moving image of at least one of the first dominant frequency and the second dominant frequency, and at least at least the first dominant frequency and the second dominant frequency over a certain period of time. The system according to any one of claims 11 to 14, wherein the system is configured to generate one corresponding to one of the changes, and the visual display includes the moving image.